Machine Learning Engineer Intern

US - AZ - Tempe, US - Remote Ref #12752 14-Mar-2023

Job Description

One team. Global challenges. Infinite opportunities. At Viasat, we’re on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We’re looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team.

Job Description

As a Machine Learning Engineer Intern, you will be part of a diverse team of engineers developing next-generation, vertically integrated products and services at Viasat. You will develop novel algorithms and techniques for analyzing complex data sets collected during Viasat’s product and service lifecycles. You will help define and develop models that produce new inferences and enable action by adjacent teams. You will work with software engineers to create new tools, libraries, and services that can expand Viasat’s ability to understand these complex data sets. You will be part of a growing team developing cloud-based solutions for tackling problems found at the cutting edge of technological development and manufacturing. 

On this team, you will build a breadth of knowledge including distributed systems, predictive analytics, and machine learning. You will design, develop, and deploy analytic pipelines to answer questions across multiple business areas and disciplines for Viasat’s broad but vertically integrated products. We encourage learning through curiosity, immersion, collaboration, and action. We value adaptability and learning agility. Our ideal candidate is someone focused on solving tough problems using data and who loves doing so.

As a Machine Learning Engineer Intern, you will contribute with:
  • Analytics: Architect, design, and build data analysis pipelines working with large and complex data sets to monitor and analyze metrics
  • Inference: Use statistical tools to design experiments and determine causality
  • Algorithms: Design and create predictive and decision-making machine learning models for various business needs
  • Data engineering: Transforming and understanding data from many systems

Requirements

  • Currently pursuing a Bachelor's degree or higher in Data Science, Applied Mathematics, Computer Science, Computer Engineering, Physics, or related field
  • Experience with several statistical and machine learning models
  • Experience with software development in Python
  • Able to commit to a 10-12 week summer internship

Preferences

  • Pursuing a MS/PhD in a data-related field such as applied mathematics, computer science, computer engineering, physics, or similar
  • Knowledge of RF engineering, RF electronics, integrated circuits, electronics manufacturing, or digital communication systems
  • Interest in or desire to work on anomaly detection, broadly defined
  • Knowledge of or Interest in learning Bayesian approaches

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Additional Requirements and Information

Minimum Education
High School Diploma or GED
Years of Experience
0-2 years
Travel
None
Citizenship
US Citizenship required
Worker Classification
Intern
At Viasat, we consider many factors when it comes to compensation, including the scope of the position as well as your background and experience. For United States-based jobs only: The pay range for this position is $19.00 to $70.00 hourly; however, base pay may vary within this range depending on location, job-related knowledge, skills, and experience. Additional cash or stock incentives may be provided as part of the compensation package, in addition to a range of medical, financial, and/or other benefits, dependent on the position offered.  Learn more about Viasat’s comprehensive benefit offerings that are focused on your holistic health and wellness.
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Viasat is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, ancestry, physical or mental disability, medical condition, marital status, genetics, age, or veteran status or any other applicable legally protected status or characteristic.

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